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Huawei H13-321_V2.0 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Overview of ModelArts | 4% | - Development and deployment workflow - ModelArts platform architecture |
| Topic 2: Speech Processing Lab Guide | 12% | - Speech application development on ModelArts |
| Topic 3: Natural Language Processing Lab Guide | 10% | - NLP project practice on ModelArts |
| Topic 4: Theoretical Knowledge and Applications of Speech Processing | 10% | - Speech processing basics - Acoustic and language models - Speech recognition and synthesis |
| Topic 5: Theoretical Knowledge and Applications of Natural Language Processing | 10% | - Text processing and representation - Common NLP tasks and applications - NLP core concepts |
| Topic 6: ModelArts Platform Development Experiment | 10% | |
| Topic 7: Theoretical Knowledge and Applications of Image Processing | 26% | - Image preprocessing and feature extraction - Computer vision overview - Convolutional neural networks - Image recognition, detection and segmentation |
| Topic 8: Image Processing Lab Guide | 12% | - ModelArts-based image development |
| Topic 9: Overview of Huawei AI Development Strategy and Full-Stack, All-Scenario AI Portfolio | 2% | |
| Topic 10: Neural Network Basics | 4% | - Artificial neural network principles - Deep learning fundamentals - Network training and optimization |
Huawei HCIP-AI-EI Developer V2.0 Sample Questions:
Question 1
What types of annotation tasks can be performed in data annotation in ModelArts data management? (Multiple choice)
A. Object Detection
B. Predictive Analytics
C. Gene sequencing
D. Image Classification
Question 2
Which of the following descriptions of gradient disappearance and gradient explosion are correct? (Multiple choice)
A. The gradient disappearance problem can be effectively solved by simple gradient clipping
B. Gradient explosion usually occurs in deep networks and when the weight initialization value is too large
C. The gradient explosion problem can be effectively solved by simple gradient clipping
D. One of the reasons for the disappearance of gradients is the use of inappropriate activation functions in deep networks, such as sigmoid
Question 3
What are the basic methods of natural language processing? (Multiple choice)
A. Strengthening Model
B. Competency Model
C. Application Model
D. Supervision Model
Question 4
Which of the following options is a hyperparameter? (Multiple choice)
A. Information entropy in decision trees
B. C in SVM
C. K in KNN
D. K in K-Means
Question 5
What is Tensorboard?
A. Deep learning visualization tool officially provided by MXNet
B. Deep learning visualization tool provided by TensorFlow
C. Visualization toolkit provided by Python
D. ModelArts' self-developed visualization tools
Solutions:
| Question 1 Answer: A,B,D | Question 2 Answer: B,C,D | Question 3 Answer: B,C | Question 4 Answer: B,C,D | Question 5 Answer: B |
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